About the Intern Program

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The 2026 summer intern program runs for 12-16 weeks from May - September. As an intern, you will contribute to meaningful projects, be mentored by industry leaders, participate in tech talks and other activities designed to support your personal and professional development. Our internships align with Autodesk’s Flexible Workplace approach, which is designed to meet the needs of our business while providing flexibility in support of office, remote and hybrid work preferences.

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Position Overview

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As an intern in Autodesk Research’s AI Lab, you will explore and apply advanced machine learning techniques to empower our customers in designing and building a better, safer, and more sustainable world. We are a team of researchers, engineers, and industry domain experts working on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction.

We are seeking an intern to join our research team focused on generative methods for content creation in the media and entertainment space. In this role, you will explore novel generative models to advance character animation through physics-based approaches. The purpose of this research is to enable intuitive and seamless use of physics within our animation tools.

Autodesk's AI Lab is actively engaged in the broader research community, targeting publications at top-tier conferences such as CVPR, NeurIPS, ICML, SIGGRAPH, and ICLR. We collaborate with top academic & industry labs, combining the best of an academic environment with product-driven research.

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Minimum Qualifications

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• Full-time student pursuing a Ph.D. in Computer Science, Computer Graphics, Computational Physics, Machine Learning or a discipline in an accredited program with at least one academic term to complete post-internship
• Broad understanding of machine learning and deep learning
• Excellent Programming and software development skills, with experience in Python, or C++
• Proficient with ML & DL platforms & libraries (PyTorch, TensorFlow, Keras, ONNX/Runtime, scikit-learn, etc.)
• Experience conducting research and publishing results
• An excellent communicator and team player

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Preferred Qualifications  

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• Deep expertise in areas such as computer graphics, 2D/3D geometry representation learning, generative models, and unsupervised/self-supervised learning
• Experience with differentiable physics, data-driven computational physics, solver-driven learning (physics-in-the-loop), physics-informed models, multi-physics, and coupled systems
• Bonus: experience with physics real-time engines (such as Bullet, Unreal, or PhysX)
• Bonus: experience with modeling tools (such as Maya, Houdini, or Blender)

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